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Mobile Phone User Authentication with Grip Gestures using Pressure Sensors

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Tsutomu HorikoshiAuthors Info & Claims

MoMM '14: Proceedings of the 12th International Conference on Advances in Mobile Computing and Multimedia

Pages 143 - 146

https://doi.org/10.1145/2684103.2684116

Published: 08 December 2014 Publication History

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Abstract

Authentication methods with password, PIN, face recognition, and fingerprint identification have widely been used, however these methods have problems of difficulty in one-handed operation, vulnerability to shoulder hacking, and illegal access using fingerprint with super glue or facial portrait. Prom viewpoint of usability and safety, strong and uncomplicated method is required. We propose a user authentication method based on grip gestures using pressure sensors mounted on the lateral and back of a mobile phone. Grip gesture is an operation of grasping a mobile phone, which is assumed to be done instead of conventional unlock procedure. Grip gesture can be performed with one hand. Moreover, it is hard to imitate grip gestures since finger movements and grip force during a grip gesture are hardly seen by the others. We experimentally investigated the feature values of grip force and evaluated our proposed method from viewpoint of error rate.

References

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K. Kim et al. Hand grip pattern recognition for mobile user interfaces. In Conf. on Innovative Applications of Artificial Intelligence, volume 2, pages 1789--1794, 2006.

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K. Sato et al. Personal authentication system based on grasping characteristics. In Japan-Korea Int'l Symposium on Kansei Engineering, number 13, 2005.

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M. Ohta et al. Individual authentication for portable devices using motion features. In Int'l Conf. on Mobile computing and Ubiquitous networking, pages 100--105, 2004.

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Q. Tao and R. Veldhuis. Biometric authentication for a mobile personal device. In Annual Int'l Conf. on Mobile and Ubiquitous Systems: Networking & Services, pages 1--3, 2006.

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T. Iso and T. Horikoshi. Statistical approaches for personal feature extraction from pressure array sensors. In IEEE Int'l Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pages 129--133, 2013.

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Cited By

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Araujo De Aguiar CHarry OStone Shi SChan Ying M(2024)Grasp the Future: Supporting Grip Strength Assistance with GripAidProceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments10.1145/3652037.3652066(169-176)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1145/3652037.3652066
Sekiguchi SKato SNishikawa YShizuki B(2024)Authentication Method Using Opening GesturesHCI for Cybersecurity, Privacy and Trust10.1007/978-3-031-61382-1_12(186-203)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-61382-1_12
Yi XZhang SPan ZShi LHan FKong YLi HShi Y(2023)Squeez’In: Private Authentication on Smartphones based on Squeezing GesturesProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581419(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581419
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Index Terms

Mobile Phone User Authentication with Grip Gestures using Pressure Sensors
1. Information systems
  1. Information systems applications

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Information

Published In

MoMM '14: Proceedings of the 12th International Conference on Advances in Mobile Computing and Multimedia

December 2014

464 pages

ISBN:9781450330084

DOI:10.1145/2684103

General Chair:
Shyue-Liang Leon Wang
National University of Kaohsiung, Taiwan
,
Program Chairs:
Yu-Hui Tao
National University of Kaohsiung, Taiwan
,
Liming Chen
University of Ulster, UK
,
Chung-Nan Lee
National Sun Yat-sen University, Taiwan

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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JKU: Johannes Kepler Universität Linz

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2014

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MoMM '14

MoMM '14: The 12th International Conference on Advances in Mobile Computing and Multimedia

December 8 - 10, 2014

Kaohsiung, Taiwan

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Cited By

View all

Araujo De Aguiar CHarry OStone Shi SChan Ying M(2024)Grasp the Future: Supporting Grip Strength Assistance with GripAidProceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments10.1145/3652037.3652066(169-176)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1145/3652037.3652066
Sekiguchi SKato SNishikawa YShizuki B(2024)Authentication Method Using Opening GesturesHCI for Cybersecurity, Privacy and Trust10.1007/978-3-031-61382-1_12(186-203)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-61382-1_12
Yi XZhang SPan ZShi LHan FKong YLi HShi Y(2023)Squeez’In: Private Authentication on Smartphones based on Squeezing GesturesProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581419(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581419
Ertam FYakut OTuncer T(2022)Pattern lock screen detection method based on lightweight deep feature extractionNeural Computing and Applications10.1007/s00521-022-07846-635:2(1549-1567)Online publication date: 30-Sep-2022
https://doi.org/10.1007/s00521-022-07846-6
Fujii AMurao K(2021)User Identification Method based on Head Shape Using Pressure Sensors Embedded in a HelmetJournal of Information Processing10.2197/ipsjjip.29.61029(610-619)Online publication date: 2021
https://doi.org/10.2197/ipsjjip.29.610
Futami KFukao AMurao KHarle RFarrahi KLane N(2019)A method to recognize entering and leaving person based on door opening and closing movement using angular velocity sensorAdjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers10.1145/3341162.3343798(57-60)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3341162.3343798
Ishida AMurao KTerada TTsukamoto M(2017)A user identification method based on features of opening/closing a refrigerator door2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2017.7917619(533-538)Online publication date: Mar-2017
https://doi.org/10.1109/PERCOMW.2017.7917619

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